Contextualization of machine indeterminable information based on machine determinable information

• US 8,600,173 B2
• Filed: 08/19/2010
• Issued: 12/03/2013
• Est. Priority Date: 01/27/2010
• Status: Expired due to Fees

• Current Assignee: DST Technologies, Inc. (SS&C Technologies Holdings Incorporated)
• Original Assignee: DST Technologies, Inc. (SS&C Technologies Holdings Incorporated)
• Inventors: Esposito, Deni, Ives, Paul M., Clark, Peter E., Gentry, Michael V.
• Primary Examiner(s): Carter, Aaron W
• Application Number:
  US12/859,328
• Publication Number:
  US 20110182500A1
• Time in Patent Office: 1,202 Days
• Field of Search: 382/224, 382/305
• US Class Current: 382/224
• CPC Class Codes: G06F 3/04886 by partitioning the display area of the touch-screen or the surface of the digitising tablet into independently controllable areas, e.g. virtual keyboards or menus
• CPC Class Codes: G06V 10/987 with the intervention of an operator
• CPC Class Codes: G06V 30/40 Document-oriented image-based pattern recognition
• CPC Class Codes: G06V 30/413 Classification of content, e.g. text, photographs or tables

Abstract

A system for contextualizing machine indeterminable information based on machine determinable information may include a memory, an interface, and a processor. The memory may store an electronic document image which may include information determinable by a machine and information indeterminable by a machine. The processor may be operative to receive, via the interface, the electronic document image. The processor may determine the machine determinable information of the electronic document image and may identify the machine indeterminable information of the electronic document image. The processor may contextualize the machine indeterminable information based on the machine determinable information. The processor may present the contextualized machine indeterminable information to the user to facilitate interpretation thereof. In response thereto, the processor may receive, via the interface, data representative of a user determination associated with the machine indeterminable information.

Claims

1. A method of contextualizing machine indeterminable information based on machine determinable information, the method comprising:

receiving an electronic document image, the electronic document image comprising at least a portion of which may be determinable by a machine, the remainder being indeterminable by a machine;

determining machine determinable information of the electronic document image;

identifying machine indeterminable information on the electronic document image;

contextualizing the machine indeterminable information based on the identified machine determinable information; and

presenting the contextualized machine indeterminable information to a user to facilitate interpretation thereof and, in response thereto, receiving data representative of a user determination associated with the machine indeterminable information.

2. The method of claim 1 further comprising storing the data representative of the user determination in a data store.

3. The method of claim 1 further comprising processing the machine indeterminable information based on the data representative of the user determination.

4. The method of claim 1 wherein the data representative of the user determination comprises an identification of the machine indeterminable information.

5. The method of claim 1 wherein the machine determinable information comprises an entity associated with the electronic document image and the machine indeterminable information comprises a document type of the electronic document image.

6. The method of claim 5 wherein contextualizing the machine indeterminable information based on the machine determinable information further comprises retrieving, from a data store, an identifier of each document type used by the entity associated with the electronic document image.

7. The method of claim 6 wherein presenting the contextualized machine indeterminable information to the user to facilitate interpretation thereof and, in response thereto, receiving the data representative of the user determination based on the machine indeterminable information further comprises presenting the identifier of each document type used by the entity and, in response thereto, receiving a selection of the document type of the electronic document image.

8. The method of claim 7 further comprising:

retrieving metadata associated with the selected document type, wherein the metadata identifies a plurality of fields of a database associated with a plurality of regions of the electronic document image; and

storing information contained with the plurality of regions of the electronic document image in the plurality of fields associated therewith.

9. The method of claim 1 further determining a routing destination of the electronic document image based on the received data representative of the user determination.

10. A method for data extraction and classification of an electronic document image, the method comprising:

receiving an electronic document image, the electronic document image comprising at least a portion of which may be determinable by a machine;

processing machine determinable information of the electronic document image to determine a plurality of document types having characteristics similar to the electronic document image and a plurality of corresponding likelihood values, wherein the likelihood value of each document type indicates a likelihood that the electronic document image is characterized by the corresponding document type;

assembling a graphical user interface which displays the electronic document image and a selector corresponding to each of the plurality of document types, wherein each selector comprises a graphical attribute indicative of the likelihood of the electronic document image being characterized by the document type corresponding to each selector;

providing the graphical user interface to a computing device; and

receiving, via the graphical user interface, a selection of the selector corresponding to the document type of the plurality of document types which characterizes the electronic document image.

11. The method of claim 10 wherein processing the electronic document image to determine the plurality of document types having characteristics similar to the electronic document image and the plurality of corresponding likelihood values further comprises:

identifying an entity associated with the electronic document image;

retrieving a plurality of document types associated with the entity; and

processing the electronic document image to determine the plurality of document types which have characteristics similar to the electronic document image and which are associated with the entity, and to determine the plurality of corresponding likelihood values, wherein each of the plurality of corresponding likelihood values indicates the likelihood that the electronic document image is characterized by the corresponding document type.

12. The method of claim 10 further comprising:

initiating an action associated with the document type of the plurality of document types corresponding to the selector of the plurality of selectors.

13. The method of claim 11 further comprising initiating an action associated with the document type of the plurality of document types corresponding to the selector of the plurality of selectors, wherein the action comprises classifying the electronic document image as associated with the entity and characterized by the document type of the plurality of document types corresponding to the selector of the plurality of selectors.

14. The method of claim 11 wherein the plurality of selectors are ordered in accordance with a frequency of use of each of the plurality of selectors for the entity.

15. The method of claim 10 further comprising:

providing, via the graphical user interface, a plurality of data fields corresponding to the document type of the plurality of document types; and

receiving, via the graphical user interface a plurality of values corresponding to the plurality of data fields.

16. The method of claim 10 further comprising displaying, via the graphical user interface, the likelihood value of each of the plurality of document types.

26. The method of claim 10 wherein the portion of the electronic document image determinable by the machine comprises an identifying mark of an entity associated with the electronic document image.

17. A system of extracting data from, and classifying, electronic document images, the system comprising:

means for receiving an electronic document image;

means for determining an entity associated with the electronic document image;

means for identifying a plurality of document types associated with the entity;

means for determining, for each of the plurality of document types, a likelihood value indicative of a likelihood that each document type characterizes the electronic document image;

means for assembling, by a processor, a graphical user interface for extracting a plurality of data items from the electronic document image, the graphical user interface comprising a plurality of selectors corresponding to the plurality of document types, wherein each of the plurality of selectors comprises a graphical attribute indicative of the likelihood value of the corresponding document type; and

means for providing the graphical user interface to an operator.

18. A system for contextualizing machine indeterminable information based on machine determinable information, the system comprising:

a memory operative to store an electronic document image, the electronic document image comprising at least a portion of which may be determinable by a machine, the remainder being indeterminable by a machine;

an interface coupled with the memory and operative to receive the electronic document image and communicate with a device of a user; and

a processor coupled with the interface and operative to receive, via the interface, the electronic document image, determine machine determinable information of the electronic document image, identify machine indeterminable information of the electronic document, contextualize the machine indeterminable information based on the machine determinable information, and provide, via the interface, the contextualized machine indeterminable information to the device of the user to facilitate interpretation thereof, and, in response thereto, receive, via the interface, data representative of a user determination associated with the machine indeterminable information.

19. The system of claim 18 wherein the processor further stores, in the memory, the data representative of the user determination.

20. The system of claim 18 wherein the processor further processes the machine indeterminable information based on the data representative of the user determination.

21. The system of claim 18 wherein the data representative of the user determination comprises an identification of the machine indeterminable information.

22. The system of claim 18 wherein the machine determinable information comprises an entity associated with the electronic document image and the machine indeterminable information comprises a document type of the electronic document image.

23. The system of claim 22 wherein the processor further receives, from the memory, an identifier of each document type used by the entity associated with the electronic document image.

24. The system of claim 23 wherein the processor further presents the identifier of each document type used by the entity and, in response thereto, receives a selection of the document type of the electronic document image.

25. The system of claim 18 wherein the processor further determines a routing destination of the electronic document image based on the received data representative of the user determination and routes the electronic document image to the determined routing destination.